People in the industrialized world are living longer and healthier lives on average than previously possible. People do still become ill and fall victim to various illnesses however. Modern medicine utilizes various treatments, substances, and devices for treating people. Some methods include the use of implantable medical devices (IMDs). IMDs include pacemakers, cardioverters, drug pumps, neurological stimulators, and other devices well known to those skilled in the art. Some other devices are ambulatory or wearable devices, allowing the patients to wear the devices external to the body, but may have a lead and/or delivery catheter implanted in the body. Examples of wearable devices include insulin pumps and spinal neurological devices to alleviate pain. IMDs and wearable devices have been increasingly used to treat neurological disorders.
Nervous system disorders affect millions of people, causing death and a degradation of life. Nervous system disorders include disorders of the central nervous system, peripheral nervous system, and mental health and psychiatric disorders. Such disorders include, for example without limitation, epilepsy, Parkinson's disease, essential tremor, dystonia, and multiple sclerosis (MS). Additionally, nervous system disorders include mental health disorders and psychiatric disorders which also affect millions of individuals and include, but are not limited to, anxiety (such as general anxiety disorder, panic disorder, phobias, post traumatic stress disorder (PTSD), and obsessive compulsive disorder (OCD), mood disorders (such as major depression, bipolar depression, and dysthymic disorder), sleep disorders (narcolepsy), obesity, and anorexia. As an example, epilepsy is the most prevalent serious neurological disease across all ages. Epilepsy is a group of neurological conditions in which a person has or is predisposed to recurrent seizures. A seizure is a clinical manifestation resulting from excessive, hypersynchronous, abnormal electrical or neuronal activity in the brain. (A neurological event is an activity that is indicative of a nervous system disorder. A seizure is a type of a neurological event). This electrical excitability of the brain may be likened to an intermittent electrical overload that manifests with sudden, recurrent, and transient changes of mental function, sensations, perceptions, and/or involuntary body movement. Because the seizures are unpredictable, epilepsy affects a person's employability, psychosocial life, and ability to operate vehicles or power equipment. It is a disorder that occurs in all age groups, socioeconomic classes, cultures, and countries. In developed countries, the age-adjusted incidence of recurrent unprovoked seizures ranges from 24/100,000 to 53/100,000 person-years and may be even higher in developing countries. In developed countries, age specific incidence is highest during the first few months of life and again after age 70. The age-adjusted prevalence of epilepsy is 5 to 8 per 1,000 (0.5% to 0.8%) in countries where statistics are available. In the United States alone, epilepsy and seizures affect 2.3 million Americans, with approximately 181,000 new cases occurring each year. It is estimated that 10% of Americans will experience a seizure in their lifetimes, and 3% will develop epilepsy by age 75.
There are various approaches in treating nervous system disorders. Treatment therapies can include any number of possible modalities alone or in combination including, for example, electrical stimulation, magnetic stimulation, drug infusion, and/or brain temperature control. Each of these treatment modalities can be operated using closed-loop feedback control. Such closed-loop feedback control techniques receive from a monitoring element a neurological signal that carries information about a symptom or a condition or a nervous system disorder. Such a neurological signal can include, for example, electrical signals (such as EEG, ECoG, and/or EKG), chemical signals, other biological signals (such as change in quantity of neurotransmitters), temperature signals, pressure signals (such as blood pressure, intracranial pressure or cardiac pressure), respiration signals, heart rate signals, pH-level signals, and peripheral nerve signals (cuff electrodes on a peripheral nerve). Monitoring elements can include, for example, recording electrodes or various types of sensors.
For example, U.S. Pat. No. 5,995,868 discloses a system for the prediction, rapid detection, warning, prevention, or control of changes in activity states in the brain of a patient. Use of such a closed-loop feed back system for treatment of a nervous system disorder may provide significant advantages in that treatment can be delivered before the onset of the symptoms of the nervous system disorder.
In the management of a nervous system disorder, it may be important to determine an extent of a neurological event, a location of the neurological event, a severity of the neurological event, and the occurrence of multiple neurological events in order to provide a delivery of a treatment or otherwise manage the neurological disorder. A patient, for example, would not benefit from a medical device system if the patient experienced a neurological event but was not administered treatment because the medical device system did not detect the neurological event. On the other hand, the patient may have adverse effects if the patient were subjected to a degree of treatment corresponding to multiple neurological events, such as seizures, even though the patient had only one neurological event in actuality. The field of medical device systems in the treatment of nervous system disorders would benefit from methods and apparatus that determine the extent, location, severity, and time of a neurological event or a plurality of neurological events.
Algorithms, methods, and systems for seizure detection and other neurological detection have been developed. Many such algorithms rely on modern computers, as may be expected. Sophisticated signal processing methods may be employed and digital signal processing (DSP) hardware may be used. Software engineers have become accustomed to using currently available computers, having ever faster processors and ever increasing memory. At the time of filing the present application, for example, Pentium 4 processors running at 3 GHz are not uncommon, even for personal use. Attempts or suggestions to shave clock cycles off algorithms, for example division algorithms, may seem quaint and somewhat antiquated.
Both floating point and fixed point division algorithms are commonly used.
While precision and range are certainly sacrificed, fixed point division is far faster than floating point division. Take for example the MC68HC11 processor, a very powerful and capable single-chip microcontroller, used by Medtronic in some IMDs including implantable neurostimulators. A fixed point integer division takes 41 clock cycles, while a floating point division takes 2911 clock cycles in the worst case. The fixed point routine is built into the circuitry of the microprocessor and returns a result and a remainder value. The floating point routine, being much more complicated, requires a subroutine that is about 209 bytes in size and returns a floating value or error indication. This subroutine further calls several other floating point subroutines, requiring more space, and adding 11 bytes to the stack.
Approximation of floating point division is far faster than floating point division but slower or about the same as fixed point division. While again something is certainly sacrificed, approximate floating point division is far faster than floating point division. This “approximation” can be done in numerous ways often involving fixed point division with a number that has been shifted or multiplied up, to allow for some precision retention at the cost of range or bit-width in fixed point.
In implantable medical devices, the clock speed is often severally restricted due to the need for long battery life in these self-powered devices, which can be measured in years. The space available for circuitry may also be severely limited. For these reasons, implantable devices have often used fixed point math.
Such implantable devices may nonetheless be required to do a great deal of computation in real time. In one example, a device sampling 8 electrical signals at 200 Hz, and running a detection algorithm that involves division, could require that once every 200th of a second the device needs to perform division on at least eight samples. A seizure detection algorithm can require just such a large number of divisions per second. It may not even be possible to perform the required number of divisions in the allotted time, using current methods, in implanted devices.
What would be desirable are methods for performing division approximation that require fewer clock cycles than current implanted medical device methods. What would be advantageous are division approximation methods that can be implemented on simple microprocessors and/or discrete logic, and that can be operated at the low power consumption levels most suited for implanted medical devices.